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The key differences between Python 2.x and Python 3.x with examples

Free-clip-art-thinkingMany novice Python users are wondering with which version of Python they should start. My answer to this question is usually something along the lines “just go with the version your favourite tutorial was written in, and check out the differences later on.”

But what if you are starting a new project and have the choice to pick? I would say there is currently no “right” or “wrong” as long as both Python 2.7.x and Python 3.x support the libraries that you are planning to use. However, it is worthwhile to have a look at the major differences between those two most popular versions of Python to avoid common pitfalls when writing the code for either one of them, or if you are planning to port your project. After looking at the differences if you are still not able to decide then this post might help.

What are the differences?

Python 3.0 was released in 2008. The final 2.x version 2.7 release came out in mid-2010, with a statement of extended support for this end-of-life release. The 2.x branch will see no new major releases after that. 3.x is under active development and has already seen over five years of stable releases, including version 3.3 in 2012, 3.4 in 2014, 3.5 in 2015, and 3.6 in 2016. This means that all recent standard library improvements, for example, are only available by default in Python 3.x.

Guido van Rossum (the original creator of the Python language) decided to clean up Python 2.x properly, with less regard for backwards compatibility than in the case for new releases in the 2.x range. The most drastic improvement is the better Unicode support (with all text strings being Unicode by default) as well as saner bytes/Unicode separation.

Besides, several aspects of the core language (such as print and exec being statements, integers using floor division) have been adjusted to be easier for newcomers to learn and to be more consistent with the rest of the language, and old cruft has been removed (for example, all classes are now new-style, “range()” returns a memory efficient iterable, not a list as in 2.x).

The What’s New in Python 3.0 document provides a good overview of the major language changes and likely sources of incompatibility with existing Python 2.x code. Nick Coghlan (one of the CPython core developers) has also created a relatively extensive FAQ regarding the transition.

However, the broader Python ecosystem has amassed a significant amount of quality software over the years. The downside of breaking backwards compatibility in 3.x is that some of that software (especially in-house software in companies) still doesn’t work on 3.x yet.

Some syntax differences :-

Division operator

If we are porting our code or executing the python 3.x code in python 2.x, it can be dangerous if integer division changes go unnoticed (since it doesn’t raise any error). It is preferred to use the floating value (like 7.0/5 or 7/5.0) to get the expected result when porting our code.

print 7 / 5
print -7 / 5   
 
'''
Output in Python 2.x
1
-2
Output in Python 3.x :
1.4
-1.4
 
'''

print function
This is the most well known change. In this the print function in Python 2.x is replaced by print() function in Python 3.x,i.e, to print in Python 3.x an extra pair of parenthesis is required.

print 'Hello, Geeks'      # Python 3.x doesn't support
print('Hope You like these facts')
 
'''
Output in Python 2.x :
Hello, Geeks
Hope You like these facts
 
Output in Python 3.x :
File "a.py", line 1
    print 'Hello, Geeks'
                       ^
SyntaxError: invalid syntax
 
'''

As we can see, if we use parenthesis in python 2.x then there is no issue but if we don’t use parenthesis in python 3.x, we get SyntaxError.

Unicode
In Python 2, implicit str type is ASCII. But in Python 3.x implicit str type is Unicode.

print(type('default string '))
print(type(b'string with b '))
 
'''
Output in Python 2.x (Bytes is same as str)
<type 'str'>
<type 'str'>
 
Output in Python 3.x (Bytes and str are different)
<class 'str'>
<class 'bytes'>
'''

Python 2.x also supports Unicode

print(type('default string '))
print(type(u'string with b '))
 
'''
Output in Python 2.x (Unicode and str are different)
<type 'str'>
<type 'unicode'>
 
Output in Python 3.x (Unicode and str are same)
<class 'str'>
<class 'str'>
'''

xrange
xrange() of Python 2.x doesn’t exist in Python 3.x. In Python 2.x, range returns a list i.e. range(3) returns [0, 1, 2] while xrange returns a xrange object i. e., xrange(3) returns iterator object which work similar to Java iterator and generates number when needed.
If we need to iterate over the same sequence multiple times, we prefer range() as range provides a static list. xrange() reconstructs the sequence every time. xrange() doesn’t support slices and other list methods. The advantage of xrange() is, it saves memory when task is to iterate over a large range.

In Python 3.x, the range function now does what xrange does in Python 2.x, so to keep our code portable, we might want to stick to using range instead. So Python 3.x’s range function is xrange from Python 2.x.

for x in xrange(1, 5):
    print(x),
 
for x in range(1, 5):
    print(x),
 
'''
Output in Python 2.x
1 2 3 4 1 2 3 4
 
Output in Python 3.x
NameError: name 'xrange' is not defined
'''

Error Handling

try:
    trying_to_check_error
except NameError, err:
    print err, 'Error Caused'   # Would not work in Python 3.x
 
'''
Output in Python 2.x:
name 'trying_to_check_error' is not defined Error Caused
 
Output in Python 3.x :
File "a.py", line 3
    except NameError, err:
                    ^
SyntaxError: invalid syntax
'''
try:
     trying_to_check_error
except NameError as err: # 'as' is needed in Python 3.x
     print (err, 'Error Caused')
 
'''
Output in Python 2.x:
(NameError("name 'trying_to_check_error' is not defined",), 'Error Caused')
 
Output in Python 3.x :
name 'trying_to_check_error' is not defined Error Caused
'''

_future_module
This is basically not a difference between two version, but useful thing to mention here. The idea of __future__ module is to help in migration. We can use Python 3.x
If we are planning Python 3.x support in our 2.x code,we can ise_future_ imports it in our code.

For example, in below Python 2.x code, we use Python 3.x’s integer division behavior using __future__ module

# In below python 2.x code, division works
# same as Python 3.x because we use  __future__
from __future__ import division
 
print 7 / 5
print -7 / 5
''' output
1.4
-1.4
'''

 
 

 

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Should I use Python 2 or Python 3 for my development activity?

thinker-28741_640Python is without any doubt one of the most talked about programming language in this Universe. It’s everywhere, and because of how simple it is to learn it – many beginners start their career with Python. The syntax of Python is very similar to that of English language, with the exception of a few extra characters here and there. Currently there are two main versions of Python, Python 2 and Python 3, that have slight differences in their syntax and their support of different libraries. You can refer this post to know the key differences between Python 2 and Python 3.

No doubt both versions of Python are good but many a times, beginners get confused while choosing one of the two for their development purpose. In this article I will try to explain which Python version can you use to start your development.

What are the differences?

Short version: Python 2.x is legacy, Python 3.x is the present and future of the language

In order to avoid making this post too long, I will be avoiding the details of differences between the two versions. The detailed post on differences between Python 2 and Python 3 can be found here.

Which version should I use?

Which version you ought to use is mostly dependent on what you want to accomplish.

If you can do exactly what you want with Python 3.x, great! There are a few minor downsides, such as very slightly bad library support and the fact that some current Linux distributions and Macs are still using 2.x as default (although Python 3 ships with many of them), but as a language Python 3.x is definitely ready. As long as Python 3.x is installed on your user’s computers (which ought to be easy, since many people reading this may only be developing something for themselves or an environment they control) and you’re writing things where you know none of the Python 2.x modules are needed, it is an excellent choice. Also, most Linux distributions have Python 3.x already installed, and available for end-users. Some are phasing out Python 2 as pre-installed default.

In particular, instructors introducing Python to new programmers should consider teaching Python 3 first and then introducing the differences in Python 2 afterwards (if necessary), since Python 3 eliminates many quirks that can unnecessarily trip up beginning programmers trying to learn Python 2.

However, there are some key issues that may require you to use Python 2 rather than Python 3.

  • Firstly, if you’re deploying to an environment you don’t control, that may impose a specific version, rather than allowing you a free selection from the available versions.
  • Secondly, if you want to use a specific third party package or utility that doesn’t have a released version that is compatible with Python 3, and porting that package is a non-trivial task, you may choose to use Python 2 in order to retain access to that package.

Python 3 already broadly supports creating GUI applications, with Tkinter in the standard library. Python 3 has been supported by PyQt almost from the day Python 3 was released; PySide added Python 3 support in 2011. GTK+ GUIs can be created with PyGObject which supports Python 3 and is the successor to PyGtk.
Many other major packages have been ported to Python 3 including:

  • NumPy and SciPy (for number crunching and scientific computing)
  • Django, Flask, CherryPy and Pyramid (for Web sites)
  • NumPy and SciPy (for number crunching and scientific computing)
  • Django, Flask, CherryPy and Pyramid (for Web sites)
  • And many, many more!

If you want to use Python 3.x, but you’re afraid to because of a dependency, it’s probably worthwhile doing some research first. This is a work in progress. Furthermore, with the large common subset supported by both Python 2.6+ and Python 3.3+, many modern Python code should run largely unmodified on Python 3, especially code written to interoperate with web and GUI frameworks that force applications to correctly distinguish binary data and text (some assistance from the six compatibility module may be needed to handle name changes).

Even though the official python documentation and the tutorial have been completely updated for Python 3, there is still a lot of documentation (including examples) on the Web and in reference books that use Python 2, although more are being updated all the time. This can require some adjustment to make things work with Python 3 instead.

Some people just don’t want to use Python 3.x, which is their prerogative. However, they are in the minority.
It is worth noting that if you wish to use an alternative implementation of Python such as IronPython, Jython or Pyston (or one of the longer list of Python platform or compiler implementations), Python 3 support is still relatively rare. This may affect you if you are interested in choosing such an implementation for reasons of integration with other systems or for performance.

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5 Top Python Frameworks For Web Developers

A Web framework can be very helpful for developers to write Web applications without having to handle low-level details as protocols, sockets or process/thread management. But a perfect choice might depend on a developer specific needs, preferences, and skill level. Python is a dynamic, object-oriented language. It was originally designed as an object-oriented language and some more advanced features were added in the later versions. In addition to the design purpose of language itself, the Python standard library is worth praising, and it even brings its own server. In other aspects, Python has enough free data library, free Web page template system and the library interacting with the Web server, which can be designed to your Web application. In this article we are going to look at 5 top Python Frameworks(according to me) for web development purpose.
1. Django

Screenshot from 2017-06-26 17-15-46
Django is a high-level Python Web framework that encourages fast growth and clean, pragmatic design. In case you are building something that’s much like a e-commerce web site, then it’s best to, in all probability, go along with Django. It would get your work executed fast. You do not have to fret about too many expertise selections. It gives the whole lot factor you want from template engine to ORM. If you wish to use your web app framework as a CMS, Django might be a more sensible choice. It’s free and open source.

2. Flask
Screenshot from 2017-06-26 17-22-07
Flask Python framework is highly extensible. A newbie programmer may find Flask inefficient due to lack of features like form validation, and database abstraction layer. In such a case, know that Flask allows you to implement extensions; therefore, you can add any required functionality.

3. CherryPy
Screenshot from 2017-06-26 17-28-40
CherryPy is a Web application development framework based on Python, that greatly simplifies the work of Python Web developers. It provides a friendly HTTP protocol interfaces for Python developers. CherryPy has a built in HTTP server or Web server, so the users of CherryPy can directly run CherryPy application without building Web server.

4. Pyramid
Screenshot from 2017-06-26 17-30-23
Pyramid is an open source, Python web application development framework. Its primary goal is to make it easier for a Python developer to create web applications. Pyramid is similar to Flask . Pyramid is compatible with python3, with a great documentation, its minimal, fast and flexible and has an integration of nosql: mongodb, couchdb . Pyramid is best for Developers working on API projects, prototyping a concept & developing large web applications, such as a CMS.

5. Web2py
Screenshot from 2017-06-26 20-13-12
Web2py is a free open source full-stack framework for rapid development of fast, scalable, secure and portable database-driven web-based applications. Written and programmable in Python.